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Conference Paper: Simulation Analytics For Emergency Medical Services
| Title | Simulation Analytics For Emergency Medical Services |
|---|---|
| Authors | |
| Issue Date | 2018 |
| Citation | The 29th European Conference On Operational Research (EURO 2018), Valencia, Spain, 8-11 July 2018 How to Cite? |
| Abstract | In this talk, I will present our collaborative project with an emergencydepartment in Hong Kong on analyzing their patient flows and systemefficiency. A simulation model that captures all complicating factors inreality (e.g., time and category-dependent arrival rates of patients, mul-tiple shift-times of doctors and re-entrant flows to the many 'servicestations' of the system) has been developed to examine possible solu-tions that could relieve the overcrowding situation. I will discuss thechallenge that several key types of data were unavailable such that thestochastic components in the system could not be directly estimated.Computational results show that our simulation model can produce re-sults consistent with the actual observations. I will also discuss someinsights, derived from the simulation results, into managing ED oper-ations. |
| Description | TB-28 - Service systems - Stream: Service Operations Management |
| Persistent Identifier | http://hdl.handle.net/10722/268700 |
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Kuo, YH | - |
| dc.contributor.author | Leung, J | - |
| dc.contributor.author | Graham, C | - |
| dc.date.accessioned | 2019-03-27T03:07:05Z | - |
| dc.date.available | 2019-03-27T03:07:05Z | - |
| dc.date.issued | 2018 | - |
| dc.identifier.citation | The 29th European Conference On Operational Research (EURO 2018), Valencia, Spain, 8-11 July 2018 | - |
| dc.identifier.uri | http://hdl.handle.net/10722/268700 | - |
| dc.description | TB-28 - Service systems - Stream: Service Operations Management | - |
| dc.description.abstract | In this talk, I will present our collaborative project with an emergencydepartment in Hong Kong on analyzing their patient flows and systemefficiency. A simulation model that captures all complicating factors inreality (e.g., time and category-dependent arrival rates of patients, mul-tiple shift-times of doctors and re-entrant flows to the many 'servicestations' of the system) has been developed to examine possible solu-tions that could relieve the overcrowding situation. I will discuss thechallenge that several key types of data were unavailable such that thestochastic components in the system could not be directly estimated.Computational results show that our simulation model can produce re-sults consistent with the actual observations. I will also discuss someinsights, derived from the simulation results, into managing ED oper-ations. | - |
| dc.language | eng | - |
| dc.relation.ispartof | The European Conference On Operational Research | - |
| dc.title | Simulation Analytics For Emergency Medical Services | - |
| dc.type | Conference_Paper | - |
| dc.identifier.email | Kuo, YH: yhkuo@hku.hk | - |
| dc.identifier.authority | Kuo, YH=rp02314 | - |
| dc.identifier.hkuros | 287478 | - |